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通过爪的X射线衍射进行犬癌诊断

Alexander Alekseev¹, Delvin Yuk², Alexander Lazarev²

¹Matur UK Ltd., 5 New Street Square, London EC4A 3TW, UK.

|July 13, 2024

概括

这项研究证明了狗爪的X射线衍射 (XRD) 用于非侵入性癌症检测. 开发的算法在识别狗癌症方面显示出高准确度,提供了一个有前途的新诊断工具.

科学领域:

兽医医学兽医医学兽医医学
生物物理学的生物物理.
机器学习机器学习

背景情况:

早期发现狗癌症对于有效治疗至关重要.
非侵入性诊断方法是非常理想的,以减少动物的压力和提高遵守.
X射线衍射 (XRD) 具有分析生物结构的潜力.

研究的目的:

调查使用狗爪的X射线衍射 (XRD) 模式用于早期,非侵入性癌症检测的可行性.
开发和验证用于分析XRD数据的机器学习算法,以诊断狗的癌症.

主要方法:

从狗的爪子收集了二维X射线衍射 (XRD) 图案.
从辐射和圆形方向的XRD图案计算了富里埃系数.
利用监督学习算法,优化随机森林分类器与训练数据.
对于一个盲人数据集,每个患者的癌症概率的计算平均值.

主要成果:

该算法在68只狗的盲人组中实现了85%的平衡精度和0.91的ROC-AUC.
从样本分析到患者分析的过渡使ROC-AUC提高了10%.
最佳的特异性和灵敏度分别为97.4%和72.4%.
分子间距离被确定为诊断的关键结构生物标志物.

结论:

狗爪的X射线衍射 (XRD) 是一种早期,非侵入性癌症检测的可行方法.
开发的机器学习方法在犬癌症中表现出高的诊断性能.
爪子结构中的分子间距离作为狗癌症诊断的重要生物标志物.

关键词:

在ROC曲线上,ROC曲线在X射线中,X射线的衍射效果是不同的.狗的癌症狗的癌症早期的癌症诊断早期的癌症诊断质素结构质素结构结构生物标志物结构生物标志物

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